DUMP DATA-ENGINEER-ASSOCIATE FILE, DATA-ENGINEER-ASSOCIATE HOTTEST CERTIFICATION

Dump Data-Engineer-Associate File, Data-Engineer-Associate Hottest Certification

Dump Data-Engineer-Associate File, Data-Engineer-Associate Hottest Certification

Blog Article

Tags: Dump Data-Engineer-Associate File, Data-Engineer-Associate Hottest Certification, Data-Engineer-Associate Valid Braindumps Questions, Exam Discount Data-Engineer-Associate Voucher, Data-Engineer-Associate Valid Exam Practice

Our company is professional brand. There are a lot of experts and professors in the field in our company. All the experts in our company are devoting all of their time to design the best Data-Engineer-Associatetest question for all people. In order to ensure quality of the products, a lot of experts keep themselves working day and night. We can make sure that you cannot find the more suitable Data-Engineer-Associatecertification guide than our study materials, so hurry to choose the study materials from our company as your study tool, it will be very useful for you to prepare for the Data-Engineer-Associate exam.

Our AWS Certified Data Engineer - Associate (DEA-C01) exam question has been widely praised by all of our customers in many countries and our company has become the leader in this field. Our product boost varied functions and they include the self-learning and the self-assessment functions, the timing function and the function to stimulate the exam to make you learn efficiently and easily. There are many advantages of our Data-Engineer-Associate Study Tool. To understand the details of our product you have to read the introduction of our product as follow firstly.

>> Dump Data-Engineer-Associate File <<

Renowned Data-Engineer-Associate Guide Exam: AWS Certified Data Engineer - Associate (DEA-C01) Carry You High-efficient Practice Materials

The desktop AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) practice exam software helps its valued customer to be well aware of the pattern of the real Data-Engineer-Associate exam. You can try a free AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) demo too. This AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) practice test is customizable and you can adjust its time and AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) exam questions.

Amazon AWS Certified Data Engineer - Associate (DEA-C01) Sample Questions (Q23-Q28):

NEW QUESTION # 23
A company receives .csv files that contain physical address data. The data is in columns that have the following names: Door_No, Street_Name, City, and Zip_Code. The company wants to create a single column to store these values in the following format:

Which solution will meet this requirement with the LEAST coding effort?

  • A. Use AWS Glue DataBrew to read the files. Use the NEST TO MAP transformation to create the new column.
  • B. Write a Lambda function in Python to read the files. Use the Python data dictionary type to create the new column.
  • C. Use AWS Glue DataBrew to read the files. Use the PIVOT transformation to create the new column.
  • D. Use AWS Glue DataBrew to read the files. Use the NEST TO ARRAY transformation to create the new column.

Answer: A

Explanation:
The NEST TO MAP transformation allows you to combine multiple columns into a single column that contains a JSON object with key-value pairs. This is the easiest way to achieve the desired format for the physical address data, as you can simply select the columns to nest and specify the keys for each column. The NEST TO ARRAY transformation creates a single column that contains an array of values, which is not thesame as the JSON object format. The PIVOT transformation reshapes the data by creating new columns from unique values in a selected column, which is not applicable for this use case. Writing a Lambda function in Python requires more coding effort than using AWS Glue DataBrew, which provides a visual and interactive interface for data transformations. References:
7 most common data preparation transformations in AWS Glue DataBrew (Section: Nesting and unnesting columns) NEST TO MAP - AWS Glue DataBrew (Section: Syntax)


NEW QUESTION # 24
A company is developing an application that runs on Amazon EC2 instances. Currently, the data that the application generates is temporary. However, the company needs to persist the data, even if the EC2 instances are terminated.
A data engineer must launch new EC2 instances from an Amazon Machine Image (AMI) and configure the instances to preserve the data.
Which solution will meet this requirement?

  • A. Launch new EC2 instances by using an AMI that is backed by an EC2 instance store volume. Attach an Amazon Elastic Block Store (Amazon EBS) volume to contain the application data. Apply the default settings to the EC2 instances.
  • B. Launch new EC2 instances by using an AMI that is backed by an EC2 instance store volume that contains the application data. Apply the default settings to the EC2 instances.
  • C. Launch new EC2 instances by using an AMI that is backed by a root Amazon Elastic Block Store (Amazon EBS) volume that contains the application data. Apply the default settings to the EC2 instances.
  • D. Launch new EC2 instances by using an AMI that is backed by an Amazon Elastic Block Store (Amazon EBS) volume. Attach an additional EC2 instance store volume to contain the application data. Apply the default settings to the EC2 instances.

Answer: A

Explanation:
Amazon EC2 instances can use two types of storage volumes: instance store volumes and Amazon EBS volumes. Instance store volumes are ephemeral, meaning they are only attached to the instance for the duration of its life cycle. If the instance is stopped, terminated, or fails, the data on the instance store volume is lost. Amazon EBS volumes are persistent, meaning they can be detached from the instance and attached to another instance, and the data on the volume is preserved. To meet the requirement of persisting the data even if the EC2 instances are terminated, the data engineer must use Amazon EBS volumes to store the application data. The solution is to launch new EC2 instances by using an AMI that is backed by an EC2 instance store volume, which is the default option for most AMIs. Then, the data engineer must attach an Amazon EBS volume to each instance and configure the application to write the data to the EBS volume. This way, the data will be saved on the EBS volume and can be accessed by another instance if needed. The data engineer can apply the default settings to the EC2 instances, as there is no need to modify the instance type, security group, or IAM role for this solution. The other options are either not feasible or not optimal. Launching new EC2 instances by using an AMI that is backed by an EC2 instance store volume that contains the application data (option A) or by using an AMI that is backed by a root Amazon EBS volume that contains the application data (option B) would not work, as the data on the AMI would be outdated and overwritten by the new instances. Attaching an additional EC2 instance store volume to contain the application data (option D) would not work, as the data on the instance store volume would be lost if the instance is terminated. References:
* Amazon EC2 Instance Store
* Amazon EBS Volumes
* AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 2: Data Store Management, Section 2.1: Amazon EC2


NEW QUESTION # 25
A company has a frontend ReactJS website that uses Amazon API Gateway to invoke REST APIs. The APIs perform the functionality of the website. A data engineer needs to write a Python script that can be occasionally invoked through API Gateway. The code must return results to API Gateway.
Which solution will meet these requirements with the LEAST operational overhead?

  • A. Deploy a custom Python script that can integrate with API Gateway on Amazon Elastic Kubernetes Service (Amazon EKS).
  • B. Deploy a custom Python script on an Amazon Elastic Container Service (Amazon ECS) cluster.
  • C. Create an AWS Lambda function. Ensure that the function is warm byscheduling an Amazon EventBridge rule to invoke the Lambda function every 5 minutes by usingmock events.
  • D. Create an AWS Lambda Python function with provisioned concurrency.

Answer: D

Explanation:
AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers.
You can use Lambda to create functions that perform custom logic and integrate with other AWS services, such as API Gateway. Lambda automatically scales your application by running code in response to each trigger. You pay only for the compute time you consume1.
Amazon ECS is a fully managed container orchestration service that allows you to run and scale containerized applications on AWS. You can use ECS to deploy, manage, and scale Docker containers using either Amazon EC2 instances or AWS Fargate, a serverless compute engine for containers2.
Amazon EKS is a fully managed Kubernetes service that allows you to run Kubernetes clusters on AWS without needing to install, operate, or maintain your own Kubernetes control plane. You can use EKS to deploy, manage, and scale containerized applications using Kubernetes on AWS3.
The solution that meets the requirements with the least operational overhead is to create an AWS Lambda Python function with provisioned concurrency. This solution has the following advantages:
It does not require you to provision, manage, or scale any servers or clusters, as Lambda handles all the infrastructure for you. This reduces the operational complexity and cost of running your code.
It allows you to write your Python script as a Lambda function and integrate it with API Gateway using a simple configuration. API Gateway can invoke your Lambda function synchronously or asynchronously, and return the results to the frontend website.
It ensures that your Lambda function is ready to respond to API requests without any cold start delays, by using provisioned concurrency. Provisioned concurrency is a feature that keeps your function initialized and hyper-ready to respond in double-digit milliseconds. You can specify the number of concurrent executions that you want to provision for your function.
Option A is incorrect because it requires you to deploy a custom Python script on an Amazon ECS cluster.
This solution has the following disadvantages:
It requires you to provision, manage, and scale your own ECS cluster, either using EC2 instances or Fargate. This increases the operational complexity and cost of running your code.
It requires you to package your Python script as a Docker container image and store it in a container registry, such as Amazon ECR or Docker Hub. This adds an extra step to your deployment process.
It requires you to configure your ECS cluster to integrate with API Gateway, either using an Application Load Balancer or a Network Load Balancer. This adds another layer of complexity to your architecture.
Option C is incorrect because it requires you to deploy a custom Python script that can integrate with API Gateway on Amazon EKS. This solution has the following disadvantages:
It requires you to provision, manage, and scale your own EKS cluster, either using EC2 instances or Fargate. This increases the operational complexity and cost of running your code.
It requires you to package your Python script as a Docker container image and store it in a container registry, such as Amazon ECR or Docker Hub. This adds an extra step to your deployment process.
It requires you to configure your EKS cluster to integrate with API Gateway, either using an Application Load Balancer, a Network Load Balancer, or a service of type LoadBalancer. This adds another layer of complexity to your architecture.
Option D is incorrect because it requires you to create an AWS Lambda function and ensure that the function is warm by scheduling an Amazon EventBridge rule to invoke the Lambda function every 5 minutes by using mock events. This solution has the following disadvantages:
It does not guarantee that your Lambda function will always be warm, as Lambda may scale down your function if it does not receive any requests for a long period of time. This may cause cold start delays when your function is invoked by API Gateway.
It incurs unnecessary costs, as you pay for the compute time of your Lambda function every time it is invoked by the EventBridge rule, even if it does not perform any useful work1.
References:
1: AWS Lambda - Features
2: Amazon Elastic Container Service - Features
3: Amazon Elastic Kubernetes Service - Features
[4]: Building API Gateway REST API with Lambda integration - Amazon API Gateway
[5]: Improving latency with Provisioned Concurrency - AWS Lambda
[6]: Integrating Amazon ECS with Amazon API Gateway - Amazon Elastic Container Service
[7]: Integrating Amazon EKS with Amazon API Gateway - Amazon Elastic Kubernetes Service
[8]: Managing concurrency for a Lambda function - AWS Lambda


NEW QUESTION # 26
A company wants to implement real-time analytics capabilities. The company wants to use Amazon Kinesis Data Streams and Amazon Redshift to ingest and process streaming data at the rate of several gigabytes per second. The company wants to derive near real-time insights by using existing business intelligence (BI) and analytics tools.
Which solution will meet these requirements with the LEAST operational overhead?

  • A. Use Kinesis Data Streams to stage data in Amazon S3. Use the COPY command to load data from Amazon S3 directly into Amazon Redshift to make the data immediately available for real-time analysis.
  • B. Create an external schema in Amazon Redshift to map the data from Kinesis Data Streams to an Amazon Redshift object. Create a materialized view to read data from the stream. Set the materialized view to auto refresh.
  • C. Connect Kinesis Data Streams to Amazon Kinesis Data Firehose. Use Kinesis Data Firehose to stage the data in Amazon S3. Use the COPY command to load the data from Amazon S3 to a table in Amazon Redshift.
  • D. Access the data from Kinesis Data Streams by using SQL queries. Create materialized views directly on top of the stream. Refresh the materialized views regularly to query the most recent stream data.

Answer: B

Explanation:
This solution meets the requirements of implementing real-time analytics capabilities with the least operational overhead. By creating an external schema in Amazon Redshift, you can access the data from Kinesis Data Streams using SQL queries without having to load the data into the cluster. By creating a materialized view on top of the stream, you can store the results of the query in the cluster and make them available for analysis. By setting the materialized view to auto refresh, you can ensure that the view is updated with the latest data from the stream at regular intervals. This way, you can derive near real-time insights by using existing BI and analytics tools. References:
Amazon Redshift streaming ingestion
Creating an external schema for Amazon Kinesis Data Streams
Creating a materialized view for Amazon Kinesis Data Streams


NEW QUESTION # 27
A company is migrating on-premises workloads to AWS. The company wants to reduce overall operational overhead. The company also wants to explore serverless options.
The company's current workloads use Apache Pig, Apache Oozie, Apache Spark, Apache Hbase, and Apache Flink. The on-premises workloads process petabytes of data in seconds. The company must maintain similar or better performance after the migration to AWS.
Which extract, transform, and load (ETL) service will meet these requirements?

  • A. Amazon Redshift
  • B. Amazon EMR
  • C. AWS Lambda
  • D. AWS Glue

Answer: B

Explanation:
AWS Glue is a fully managed serverless ETL service that can handle petabytes of data in seconds. AWS Glue can run Apache Spark and Apache Flink jobs without requiring any infrastructure provisioning or management. AWS Glue can also integrate with Apache Pig, Apache Oozie, and Apache Hbase using AWS Glue Data Catalog and AWS Glue workflows. AWS Glue can reduce the overall operational overhead by automating the data discovery, data preparation, and data loading processes. AWS Glue can also optimize the cost and performance of ETL jobs by using AWS Glue Job Bookmarking, AWS Glue Crawlers, and AWS Glue Schema Registry. Reference:
AWS Glue
AWS Glue Data Catalog
AWS Glue Workflows
[AWS Glue Job Bookmarking]
[AWS Glue Crawlers]
[AWS Glue Schema Registry]
[AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide]


NEW QUESTION # 28
......

Dumps4PDF is constantly updated in accordance with the changing requirements of the Amazon certification. We arrange the experts to check the update every day, if there is any update about the Data-Engineer-Associate pdf vce, the latest information will be added into the Data-Engineer-Associate exam dumps, and the useless questions will be remove of it to relief the stress for preparation. Al the effort our experts have done is to ensure the high quality of the Data-Engineer-Associate Study Material. You will get your Data-Engineer-Associate certification with little time and energy by the help of out dumps.

Data-Engineer-Associate Hottest Certification: https://www.dumps4pdf.com/Data-Engineer-Associate-valid-braindumps.html

Amazon Dump Data-Engineer-Associate File printable versionHide Answer Sales tax is only assessed for orders placed by customers in Tennessee and Florida, Secondly, our workers have checked the Data-Engineer-Associate test engine files for a lot of times, So you will get the latest Data-Engineer-Associate guide torrent materials whenever you decide to take it, After years of hard work, the experts finally developed a set of perfect learning materials Data-Engineer-Associate practice materials that would allow the students to pass the exam easily.

If you don't want to miss out on such a good Data-Engineer-Associate opportunity, buy it quickly, We use a variety of practical, real-world case studies toillustrate the nature of systems and the system Exam Discount Data-Engineer-Associate Voucher development process, and we include system models that can be used in the process.

Free PDF Amazon - Data-Engineer-Associate Fantastic Dump File

printable versionHide Answer Sales tax is only assessed for orders placed by customers in Tennessee and Florida, Secondly, our workers have checked the Data-Engineer-Associate Test Engine files for a lot of times.

So you will get the latest Data-Engineer-Associate guide torrent materials whenever you decide to take it, After years of hard work, the experts finally developed a set of perfect learning materials Data-Engineer-Associate practice materials that would allow the students to pass the exam easily.

In order to make customer purchase relieved, we guarantee you "Pass Guaranteed" with our Amazon Data-Engineer-Associate real questions.

Report this page